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Record W4366597451 · doi:10.3390/biom13040695

Connecting Dots between Mitochondrial Dysfunction and Depression

2023· review· en· W4366597451 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueBiomolecules · 2023
Typereview
Languageen
FieldNeuroscience
TopicTryptophan and brain disorders
Canadian institutionsUniversité de Moncton
FundersNatural Sciences and Engineering Research Council of CanadaNew Brunswick Innovation FoundationFondation de la recherche en santé du Nouveau-Brunswick
KeywordsOxidative stressNeuroinflammationDepression (economics)MitochondrionPathophysiologyNeuroscienceApoptosisNeuroplasticityDiseaseBiologyMedicineBioinformaticsCell biologyInternal medicineEndocrinologyBiochemistry

Abstract

fetched live from OpenAlex

homeostasis. Depression is a psychiatric disease characterized by alteration in the metabolism, neurotransmission and neuroplasticity. In this manuscript, we summarize the recent evidence linking mitochondrial dysfunction to the pathophysiology of depression. Impaired expression of mitochondria-related genes, damage to mitochondrial membrane proteins and lipids, disruption of the electron transport chain, higher oxidative stress, neuroinflammation and apoptosis are all observed in preclinical models of depression and most of these parameters can be altered in the brain of patients with depression. A deeper knowledge of the depression pathophysiology and the identification of phenotypes and biomarkers with respect to mitochondrial dysfunction are needed to help early diagnosis and the development of new treatment strategies for this devastating disorder.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.995
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.098
GPT teacher head0.348
Teacher spread0.250 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it